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污水基于疾病监测的污水系统采样:这项工作值得做吗?

Sewer system sampling for wastewater-based disease surveillance: Is the work worth it?

机构信息

Leibniz University Hannover, Welfengarten 1, 30459 Hannover, Germany.

Hamburg University of Applied Sciences, lmenliet 20, 21033 Hamburg, Germany.

出版信息

J Water Health. 2024 Nov;22(11):2218-2232. doi: 10.2166/wh.2024.301. Epub 2024 Oct 23.

Abstract

Wastewater treatment plant (WWTP) influent sampling is commonly used in wastewater-based disease surveillance to assess the circulation of pathogens in the population aggregated in a catchment area. However, the signal can be lost within the sewer network due to adsorption, degradation, and dilution processes. The present work aimed to investigate the dynamics of SARS-CoV-2 concentration in three sub-catchments of the sewer system in the city of Hildesheim, Germany, characterised by different levels of urbanisation and presence/absence of industry, and to evaluate the benefit of sub-catchment sampling compared to WWTP influent sampling. Our study shows that sampling and analysis of virus concentrations in sub-catchments with particular settlement structures allows the identification of high concentrations of the virus at a local level in the wastewater, which are lower in samples collected at the inlet of the treatment plant covering the whole catchment. Higher virus concentrations per inhabitant were found in the sub-catchments in comparison to the inlet of the WWTP. Additionally, sewer sampling provides spatially resolved concentrations of SARS-CoV-2 in the catchment area, which is important for detecting local high incidences of COVID-19.

摘要

污水处理厂(WWTP)进水采样常用于基于污水的疾病监测,以评估在集水区内聚集的人群中病原体的循环情况。然而,由于吸附、降解和稀释等过程,信号可能会在污水管网中丢失。本研究旨在调查德国希尔德斯海姆市三个污水系统子流域中 SARS-CoV-2 浓度的动态变化,这些子流域的城市化程度和工业存在/缺失情况不同,并评估与 WWTP 进水采样相比,子流域采样的优势。我们的研究表明,对具有特殊沉降结构的子流域进行病毒浓度采样和分析,可以在当地污水中识别出高浓度的病毒,而在覆盖整个集水区的处理厂入口处采集的样本中,病毒浓度则较低。与 WWTP 入口相比,每个居民的病毒浓度在子流域中更高。此外,污水采样提供了流域内 SARS-CoV-2 的空间分辨率浓度,这对于检测 COVID-19 的局部高发非常重要。

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